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115 Effects of L2 proficiency and gender on choice of language learning strategies by university students majoring in English Adel Abu Radwan [email protected] Bio Data: Dr. Radwan received his Doctorate in applied linguistics from Georgetown University in Washington, DC. He worked as an adjunct professor at George Mason University in Virginia, USA. He is currently an assistant professor at Sultan Qaboos University in Oman, where he teaches courses in psycholinguistics, language acquisition, and theoretical linguistics. Dr Radwan’s chief interest is investigating the role of metacognition in language learning and pedagogy. Abstract This study investigates the use of language learning strategies by 128 students majoring in English at Sultan Qaboos University (SQU) in Oman. Using Oxford's (1990) Strategy Inventory for Language Learners (SILL), the study seeks to extend our current knowledge by examining the relationship between the use of language learning strategies (LLS) and gender and English proficiency, measured using a three-way criteria: students' grade point average (GPA) in English courses, study duration in the English Department, and students’ perceived self-rating. It is as well a response to a call by Oxford to examine the relationship between LLSs and various factors in a variety of settings and cultural backgrounds (see Oxford, 1993). Results of a one-way analysis of variance (ANOVA) showed that the students used metacognitive strategies significantly more than any other category of strategies, with memory strategies ranking last on students' preference scale. Contrary to the findings of a number of studies (see e.g., Hong-Nam & Leavell, 2006), male students used more social strategies than female students, thus creating the only difference between the two groups in terms of their strategic preferences. Moreover, ANOVA results revealed that more proficient students used more cognitive, metacognitive and affective strategies than less proficient students. As for study duration, the results showed a curvilinear relationship between strategy use and study duration, where freshmen used more strategies followed by juniors, then

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Page 1: Effects of L2 proficiency and gender on choice of language ...asian-efl-journal.com/PDF/March-2011-aar.pdf115 Effects of L2 proficiency and gender on choice of language learning strategies

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Effects of L2 proficiency and gender on choice of language learning

strategies by university students majoring in English

Adel Abu [email protected]

Bio Data:Dr. Radwan received his Doctorate in applied linguistics from GeorgetownUniversity in Washington, DC. He worked as an adjunct professor at George MasonUniversity in Virginia, USA. He is currently an assistant professor at Sultan QaboosUniversity in Oman, where he teaches courses in psycholinguistics, languageacquisition, and theoretical linguistics. Dr Radwan’s chief interest is investigatingthe role of metacognition in language learning and pedagogy.

AbstractThis study investigates the use of language learning strategies by 128 studentsmajoring in English at Sultan Qaboos University (SQU) in Oman. Using Oxford's(1990) Strategy Inventory for Language Learners (SILL), the study seeks to extendour current knowledge by examining the relationship between the use of languagelearning strategies (LLS) and gender and English proficiency, measured using athree-way criteria: students' grade point average (GPA) in English courses, studyduration in the English Department, and students’ perceived self-rating. It is as wella response to a call by Oxford to examine the relationship between LLSs and variousfactors in a variety of settings and cultural backgrounds (see Oxford, 1993). Resultsof a one-way analysis of variance (ANOVA) showed that the students usedmetacognitive strategies significantly more than any other category of strategies,with memory strategies ranking last on students' preference scale. Contrary to thefindings of a number of studies (see e.g., Hong-Nam & Leavell, 2006), malestudents used more social strategies than female students, thus creating the onlydifference between the two groups in terms of their strategic preferences. Moreover,ANOVA results revealed that more proficient students used more cognitive,metacognitive and affective strategies than less proficient students. As for studyduration, the results showed a curvilinear relationship between strategy use andstudy duration, where freshmen used more strategies followed by juniors, then

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seniors and sophomores, respectively. Analysis of the relationship between strategyuse and self-rating revealed a sharp contrast between learners who are self-efficacious and those who are not, favoring the first group in basically every strategycategory. To find out which type of strategy predicted learners' L2 proficiency, abackward stepwise logistic regression analysis was performed on students’ data,revealing that use of cognitive strategies was the only predictor that distinguishedbetween students with high GPAs and those with low GPAs. The present studysuggests that the EFL cultural setting may be a factor that determines the type ofstrategies preferred by learners. This might be specifically true since some of theresults obtained in this study vary from results of studies conducted in other culturalcontexts. Results of this study may be used to inform pedagogical choices atuniversity and even pre-university levels.

Keywords: language learning strategies, metacognitive strategies, cognitive

strategies, gender, proficiency, self-efficacy.

Introduction

Recently, the field of English as a Foreign Language (EFL) has witnessed a gradual

shift among language educators towards student-centered approaches, leading to

numerous studies investigating the impact of socio-cultural, psychological,

cognitive, and affective variables on achievement in learning second/foreign

languages (Nunan, 1988; Brown, 2000). Educators and researchers alike have

considered these variables to be the source of discrepancies among second language

learners in their learning outcomes. Increased interest in the role of these variables

has led to numerous studies investigating individual learning styles and language

learning strategies (LLS) and their relationship to success in learning a second

language (Green & Oxford, 1995; Griffiths & Parr, 2001; Khalil, 2005; Hsiao &

Oxford, 2002; Wharton, 2000). Applied research on learning strategies had two

major goals:

(1) [to] identify and compare the learning strategies used by more and

less successful language learners, and (2) [to] provide instruction to less

successful learners that helps them become more successful in their

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language study. (Chamot, 2001, pp. 25-26)

Overall, research on the use of learning strategies (see e.g., Dreyer & Oxford,

1996; Grenfell & Harris, 1999; Harris, 2003; Park, 1997; Wharton, 2000) suggests

that language learners, whether consciously or unconsciously, utilize a variety of

learning strategies. Successful language learners, however, employ more effective

and diverse language learning strategies than less successful learners. Chamot (2004

p. 14) stated that strategic language learners possess “metacognitive knowledge

about their own thinking and learning approaches, a good understanding of what a

task entails, and the ability to orchestrate the strategies that best meet both the task

demands and their own strengths.” Accordingly, in order to help second language

learners in general and less successful learners in particular, researchers have

recommended integrating strategy training into language curricula (Chamot &

Kupper, 1989; Tyacke, 1991).

Despite the preponderance of research on language learning strategies within

English as a second language context, there is an apparent paucity of this type of

research within the Arabic EFL context. A very small number of studies (see, e.g.,

Al-Otaibi, 2004; El-Dib, 2004; Khalil, 2005; Kaylani, 1996; Shmais, 2003)

examined the use of learning strategies by students in the Arab World, with only two

studies (Al-Otaibi, 2004; El-Dib, 2004), investigating the use of LLSs in the Arab

Gulf states of Saudi Arabia and Kuwait respectively. However, no research on LLSs

has been conducted within the context of the Gulf state of Oman. In this regard, and

as Park (1997) remarked, there is a need for additional research in this area to

determine whether the patterns of strategy use that exist in a particular linguistic

setting are unique to that setting or common to all linguistic and cultural contexts.

In Oman, although Arabic is the official language, English has a special status; all

government publications and correspondences are normally written in both

languages. Moreover, English functions as a common language for communication

with the large population of expatriates working in Oman. More importantly,

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English is a compulsory subject from the first grade, and it is the primary medium of

instruction at the majority of universities. Despite its pivotal role, students at SQU,

due to their limited proficiency in English, do not usually perform well in the

English prerequisites, which negatively affects their performance in content-based

courses. Since there is a substantial body of evidence to support the positive

contribution of learning strategies to improvement in learning a foreign language, an

examination of how students in the Omani context utilize these strategies is very

critical.

Hence, the aim of the current study is to fill the gap in this area of research by

exploring the use of language learning strategies used by Omani students, and it is,

as well, a response to a call to examine the relationship between LLSs and various

factors in a variety of settings and cultural backgrounds (see Oxford, 1993). More

importantly given the small number of studies that have examined the correlation

between strategy use and self-rating (one of the variables examined in this study),

there is clearly a strong need for further research in this area. Hence this study

investigates the use of learning strategies by students majoring in English at Sultan

Qaboos University in Oman, exploring in particular the relationship between

language learning strategies and a number of variables, including gender, and

language proficiency as measured by students’ GPAs, study duration, and their

perceived self-rating. Research indicates that these four variables, which are

believed to have considerable influence on the process of language learning,

contribute to considerable variability in strategy preferences (see, e.g., Green &

Oxford, 1995; Lan & Oxford, 2003; Magogwe & Oliver, 2007).

2. Literature Review

Language learning strategies (LLS) are defined as “the conscious thoughts and

actions that learners take in order to achieve a learning goal” (Chamot, 2004, p. 14).

Through repeated use, these strategies become automatic. However, learners, if

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required, can call them to conscious awareness (Chamot, 2005). This, as Littlejohn

(2008) points out, requires learners to develop some degree of meta-awareness that

would enable them to think about their thinking, and then analyze any learning task

and eventually choose the appropriate strategy required to accomplish that task.

Interest in LLSs emerged from studies that attempted to investigate the behavior

and qualities of a good and successful language learner, with a view to teaching

these qualities to less successful learners in order to make them more effective

second language learners (Chamot et al., 1999; Grenfell & Harris, 1999; Harris,

2003). Research into LLSs started with the identification and description of learning

strategies used by language learners (see e.g., Oxford, 1990; Rubin, 1987; Stern,

1975). Later, research explored the correlation between these strategies and other

learner variables such as proficiency, gender, motivation, self-efficacy, self-rating,

cultural background, and the like (see e.g., El-Dib, 2004; Green & Oxford, 1995;

Hong-Nam & Leavell, 2006; Khalil, 2005; Magogwe & Oliver, 2007; Nisbet, Tindel

& Arroyo, 2005; Shmais, 2003). More recently, research investigated how other

variables such as the task itself and the target language affect the selection and use

of learning strategies (Chamot & Keatley, 2004).

Although researchers have proposed different classifications and

conceptualizations of language learning strategies (see e.g., O’Malley & Chamot,

1990; Schmidt & Watanabe, 2001), Oxford (1990) developed the most

comprehensive, detailed and systematic taxonomy of strategies to date. Contrary to

O’Malley & Chamot (1990) who divided LLSs into three categories: cognitive,

metacognitive, and social-affective, Oxford (1990) classified them into six groups:

memory, cognitive, compensatory, metacognitive, affective, and social strategies.

Based on this broad classification, Oxford (1990) designed a strategy assessment

survey, the Strategy Inventory for Language Learning (SILL) to collect information

about learners’ use of language learning strategies. This survey was checked for

reliability and validity, producing a high reliability coefficient (.86-.95 Cronbach’s

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α) (Khalil, 2005). The fact that numerous studies established a significant

relationship between strategies and language proficiency as measured in a variety of

ways (grades, TOEFL scores, self-ratings, etc.) gives the instrument a high validity

according to Oxford & Burry-Stock (1995). Woodrow (2005 p.91), however,

questioned the reliability of the instrument, pointing out that while the scale has a

high overall reliability, there is no “evidence to support the sixfold classification of

LLSs in the SILL in the form of subclass reliabilities.”

Despite this criticism, the SILL has been widely used to assess strategy use and to

explore the effects of various variables on strategy preferences (see, e.g., D

jigunovic, 2000; Dreyer & Oxford, 1996; Khalil, 2005; Park, 1997; Yang, 1999). In

general, studies using the SILL have invariably shown significant variation in

strategy preferences due to gender, and proficiency differences. Since this study

explores the effects of these factors on strategy preferences, the following discussion

will be limited to studies that examined these variables.

Several studies have established the existence of gender differences in the use of

language learning strategies. Green & Oxford (1995) found that females use

strategies more frequently than males. Moreover, gender differences are reflected in

the type of strategy used by males and females. Female learners tend to use more

social learning strategies (Ehrman & Oxford, 1989), more conversational and input

strategies (Oxford & Nyikos, 1989), and more memory and metacognitive strategies

(Khalil, 2005) than their male counterparts. Contrary to these findings, Shmais

(2003) did not report any differences in strategy use among university-level students

as a result of gender difference. This could be attributed to the fact that the sample

for this study was university English majors who are typically more aware of the

process of learning a foreign language and of the strategies required to obtain

proficiency than other groups. Similarly, Wharton (2000) did not reveal any effects

for gender in both the number and types of strategy used by bilingual foreign

language learners in Singapore. Again, this might be attributable to the language

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learning abilities of bilingual learners which may have nullified any gender

difference.

Language learning strategies research has consistently established a positive link

between language proficiency and strategy use (e.g., Khalil, 2005; Magogwe &

Oliver, 2007; Park, 1997; Shmais, 2003), suggesting that more proficient learners

usually use more strategies than less proficient learners. Researchers have utilized a

multitude of ways to determine students’ proficiency in the foreign language

including standardized tests such as TOEFL (Arroyo, 2005), students’ GPAs in

English courses (Shmais, 2003), language achievement tests (O’Mara & Lett, 1990),

language course grades and placement examinations (Mullin, 1992), teachers’

judgments about their students (Magogwe & Oliver, 2007), duration of study

(Khalil, 2005), and self-ratings (Oxford & Nyikos, 1989). In the current study,

proficiency has been determined using multiple measures, including students’ GPAs

in English courses, duration of study in the English program, and students’ self-

rating. Lack of an appropriate standardized language assessment test and the

relatively large sample size were the main reasons for using these various measures.

It is worth noting that students’ GPAs are by far the most accurate indicator of

students’ proficiency in English, as they represent students’ performance in the

English courses taken at the Department as part of their degree requirements,

including language skills course as well as literature and linguistics courses). In this

regard, grading students’ work in the English Department focuses on language and

is normally based on given descriptors of high, good, middle and poor proficiency at

various linguistic levels.

Investigating the relationship between strategy use of Korean university students

and language proficiency, Park (1997) found a significant relationship between

SILL learning strategies and English proficiency as measured by students’ TOEFL

scores. Additionally, the study showed that cognitive and social strategies were

more predictive of TOEFL scores than other strategies. Similarly, Lan & Oxford

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(2003) found significant effects for language proficiency on Taiwanese elementary

school EFL learners’ use of metacognitive, cognitive, compensatory and affective

strategies. Contrary to these studies, Nisbet, Tindel & Arroyo (2005) showed a

minimal correlation (4% of the variation in TOEFL score) between learning

strategies and proficiency and that only one category of learning strategies

(metacognitive strategies) was significantly correlated with TOEFL score. Likewise,

Shmais (2003) revealed that students with high proficiency, as measured by their

GPAs, differed from less proficient learners only in their use of cognitive strategies.

According to Chen (1990), the relationship between strategy use and proficiency

does not always involve a simple linear correspondence between them. The study

revealed a pattern whereby more proficient learners used fewer communication

strategies although they used them more effectively than less proficient learners.

Similarly, though Magogwe & Oliver (2007) revealed a trend in strategy use

consistent with previous research, i.e. overall strategy use increases with

proficiency, they showed that this relationship is a rather a curvilinear one, where

proficiency influenced strategy use at the primary level but not at the secondary or

the tertiary level. More importantly, as Mahlobo (2003) and Halbach (2000) point

out, though many studies revealed strong correlations between strategy use and

proficiency level, no claims of causality can be established in this type of research,

i.e. “it cannot be determined whether the language proficiency comes before, after or

concurrently with strategy use” (Magogwe & Oliver, 2007, p. 340).

A small number of studies investigated the link between the duration of English

study and strategy use. Griffith (2003) reported a positive relationship between

students’ level in a private language school in New Zealand and frequency of

language learning strategy use. Likewise, Oxford & Nyikos (1989) found that years

of study significantly affect the use of learning strategies. In a study of adolescent

learners of French L2, Ramierz (1986) reported similar results. Comparing high

school students with university students, Khalil (2005) found that university students

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used more strategies than high school learners. This might be a result of the

increased demands which proficient learners encounter while communicating in the

target language.

Language learning strategies research has also examined the relationship between

self-efficacy beliefs and self-rating and strategy use. Bandura & Schunk (1981p. 31)

defined self-efficacy as “people’s judgment of their capabilities to organize and

execute courses of action required to attain designated types of performances.”

Research in this area suggests that self-efficacy beliefs correlate positively with

increased strategy use. For example, Pajares & Schunk (2001) found that learners

who believed they were capable of performing certain tasks used more cognitive and

metacognitive strategies than those who did not. According to Ching (2002), this

result may be due to the fact that highly efficacious learners are more committed to

learning L2 and working harder to avoid failure, and they usually link failure to

insufficient effort or skills. In another study, Magogwe & Oliver (2007)

demonstrated a slightly different pattern. The study showed that there was a positive,

significant but weak relationship between self-efficacy beliefs and use of language

learning strategies, which probably justifies further research in this area to examine

thoroughly the effects of this variable.

3. The Study

The present study is a response to recommendations by many researchers (e.g.,

Green & Oxford, 1995; Park, 1997, among many others) for additional research to

examine, using a reliable and valid instrument, the relationship between language

learning strategies and several factors, which are believed to influence the process of

learning a foreign language, in a variety of settings worldwide. Hence, the study

investigates the use of language learning strategies by university students majoring

in English at Sultan Qaboos University in Oman. More specifically, it explores the

effects of gender, and proficiency, as measured by students’ GPAs, duration of

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study, and self-rating on reported strategy use by these students. The study attempts

to answer the following research questions:

1. What are the most frequent language learning strategies used by Omani

students majoring in English at SQU?

2. Are there any differences in strategy use as a result of gender differences?

3. Are there any differences among learners in strategy use due to proficiency

differences as measured by their GPAs, duration of study, and self-rating?

4. Which strategies are predictive of (correlated with) L2 proficiency?

3.1 Participants

The questionnaire used in this study was distributed to 147 students majoring in

English at Sultan Qaboos University. The questionnaire was distributed to regular

classes that represent the different study durations (freshmen, sophomores, juniors,

and seniors). Only 128 students returned their questionnaires completely answered,

meeting all the study requirements. Since the questionnaires were distributed to

regular classes and due to the demography of the English Department at SQU where

the female-male ratio is approximately 2 to 1, favoring female students, the sample

was not fairly balanced, consisting of 39 males and 89 females, whose ages ranged

from 18 to 23 at the time of data collection. The subjects were freshmen (30),

sophomores (21), juniors (39), and seniors (38). By the time of this study, all

participants had received a minimum of 8 years of English as a foreign language

instruction in the pre-University stage. Despite the relatively long period of study,

the students’ command of English is generally poor. As part of the students’

bachelor degree requirements, they were required to complete 85 credit hours in

English language and literature. It should be noted that, before joining the English

Department, all applicants must pass an English language placement test, which

assesses listening, reading, writing, and grammar. On the basis of their scores,

students who pass the test are either placed in a non-credit intensive English

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program for one whole semester, or are required to register for credit courses in the

University’s Language Center, taking six courses in general language skills,

writing, and reading, two courses each.

Since there is no standardized English test available in the University to administer

to all students participating in this study, the students’ GPAs in English courses

were used as a measure of their proficiencyi. Students’ GPAs were divided into two

groups B-and-Above and C-and-below. As for self-rating, students were asked to

rate their English (listening, writing, reading, and speaking) as excellent, good, fair,

or poor; however, only a very small number of respondents rated themselves as

“excellent” and “poor”, thus resulting in the elimination of these two categories, for

their data could not be used to form two independent groups for statistical purposesii.

Thus, only two self-rating categories were retained: “Good” and “Fair.” Table (1)

demonstrates the characteristics of the sample population.

Table 1. Demographic description of participants

n %

Gender

Male 39 30.5

Female 89 69.5

Study Level

Freshman 30 23.4

Sophomore 21 16.4

Junior 39 30.5

Senior 38 29.7

GPA

B and above 57 44.5

C and below 71 55.5

Self-rating

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Good 48 47.5

Fair 80 62.5

3.2 Instrument

The study used Oxford’s (1990) Version 7.0 of the SILL, designed for EFL/ESL

learners. Due to the high reliability of this survey, it has been used widely in more

than 50 studies, assessing the frequency of strategy use by students from different

linguistic and cultural backgrounds. The SILL uses a five-point Likert-type scale

ranging from 1 (“Never or almost never true of me”) to 5 (“Always or almost always

true of me”) (see the appendices for details of the questionnaire). The taxonomy of

strategies consists of 50 statements about strategies used by language learners

covering six broad categories of strategies, each represented by a number o f items.

Consider the following examples:

1. Memory Strategies (items 1-9): These strategies help learners remember,

store and retrieve new information when there is a need for

communication. This is achieved through using words in sentences,

connecting words to mental picture of a word, grouping, and reviewing

lessons frequently (e.g., representing sounds in memory, grouping, using

physical responses).

2. Cognitive Strategies (items 10-23): These help learners understand and

produce new language through practicing, summarizing, reasoning

deductively, and analyzing (e.g., repeating, taking notes).

3. Compensatory Strategies (items 24-29): These strategies enable learners

to use the language to overcome any limitations and gaps in their linguistic

knowledge through guessing, making up new words, and using

circumlocution and synonyms (e.g., language switching, making gestures,

and seeking help).

4. Metacognitive Strategies (items 30-38): These help learners control their

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own cognition and enable them maximize learning through monitoring

their language use, planning, coordinating the learning process, and

looking for opportunities to use the language (e..g, linking new

information with old information, self-monitoring, planning, evaluating,

and seeking practice opportunities)

5. Affective Strategies (items 39-44): These strategies help learners through

lowering their anxiety levels, increasing their motivation, and controlling

their emotions (e.g., discussing feelings with others, using music to lower

anxiety).

6. Social Strategies (items 45-50): These help learners to interact,

communicate, cooperate, and empathize with others to maximize learning

(e.g., developing cultural understanding, cooperating with others).

This SILL questionnaire is used to identify the level of strategy use for each

strategy or group of strategies. Along with the survey, Oxford (1990) developed a

scale, which reflects the level of strategy usage: (1) high usage (3.5-5.0), (2)

medium usage (2.5-3.4), and (3) low usage (1.0-2.4). The SILL was accompanied

with a background questionnaire to collect demographic information about the

students (see the appendices). Information collected included students’ gender,

GPAs in English courses, and duration of study in the English Department. The

respondents were also asked to rate their English proficiency. The present study

used the English version of the SILL with translation of difficult words into Arabic.

The main reason for using the English version is that at the time of the study the

students had finished at least one year of intensive English in the Language Center at

the University, thus, gaining a good command of the language. Moreover, English is

the official language of instruction at SQU, and students are generally familiar with

filling out all types of forms in that language. According to Shmais (2003), it is

estimated that around 50 major studies utilized the English as a foreign language

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version of the questionnaire. Several researchers, however, (see, e.g., Khalil, 2005)

used a translated version of the questionnaire to “avoid any problems participants

could encounter in understanding the items and response scale” as a result of limited

English proficiency (Khalil, 2005p. 110).

3.3 Data Collection Procedure

The SILL and background questionnaires were distributed to regular classes

representing the different levels (freshmen, sophomores, juniors, and seniors) during

the regular class meetings. The class instructors, who were informed about the

nature of the questionnaire and its administration procedure, supervised the

distribution process. Both questionnaires took an average of 35 minutes to finish

under complete conditions of anonymity and confidentiality. Of the 147 distributed

questionnaires, a total of 137 questionnaires were answered completely. All

questionnaires that were not fully answered were disregarded. Moreover, nine

students who categorized their English proficiency as “excellent” or “poor” were

removed as explained before, thus leaving the total number of participants at 128

students.

Data analysis was carried out using the SPSS 15 statistical program to obtain

descriptive and inferential statistics. First, means and standard deviations of the data

were computed. Then, to determine any variation in strategy use due to gender, and

English proficiency (measured by GPA, duration of study, and self-rating), several

analyses of variance (ANOVA) were conducted to determine whether there were

any significant differences among learners with regard to strategy use. Where

significant differences were located, the post-hoc Scheffé and LSD tests were used

to determine the location of these differences. Finally, a stepwise backward

regression was used to determine which of type of strategy was predictive of success

in language learning.

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4. Results

4.1 Overall strategy use

To answer the first research question about the most frequently used strategies, the

students’ data were submitted to a one-way analysis of variance (ANOVA).

Analysis results revealed statistically significant differences (F = 27.047, p = .000)

in the overall use of strategies by all participants. Table (2) presents the rank

ordering of the strategies according to their frequency of use. As can be seen in the

table, only metacognitive strategies ranked high in use (M = 3.5-5.0). The other

strategies fell within the medium usage range ( M = 2.5-3.4). These were

compensatory strategies (M = 3.38), followed by cognitive strategies (M = 3.34),

social strategies (M = 3.24), affective strategies (3.14) respectively, and finally the

least preferred strategies, memory strategies (M = 2.99).

Table 2. Descriptive statistics for the various learning strategies and F-test

Variable Mea

n

SD Minimu

m

Maximu

m

Ran

k

F Significanc

e

Metacognitiv

e

3.85 0.69

1

1.78 5.00 1 27.04

7

0.00

compensatory 3.38 0.60

8

1.33 4.83 2

Cognitive 3.34 0.50

9

1.86 4.57 3

Social 3.24 0.74

3

1.5 5.00 4

Affective 3.14 0.68

5

1.5 5.00 5

Memory 2.99 0.56

0

1.33 4.33 6

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Total 3.32 0.69

0

1.33 5.00

In order to locate the multiple differences among the various strategy groups, a

Scheffé post-hoc test was used. Multiple comparisons revealed the following

significant differences between the different groups of strategies: (1) memory and

cognitive in favor of cognitive (p= .002), (2) memory and compensatory in favor of

compensatory (p= .000), (3) memory and metacognitive in favor of metacognitive

(p= .000), (4) cognitive and metacognitive in favor of metacognitive (p= .000), (5)

compensatory and metacognitive in favor of metacognitive (p= .000), (6) social and

metacognitive in favor of metacognitive (p= .000), and (7) affective and

metacognitive in favor of metacognitive (p= .000). Overall, these results show that

metacognitive strategies were significantly used by L2 learners more than any other

strategy. Table (3) shows the Scheffé test results.

Table 3. Scheffé results for multiple comparisons among various strategy groups

Strategy Metacognitive Compensatory Cognitive Social Affective Memory

Metacognitive .000 .000 .000 .000 .000

Compensatory .999 .692 .140 .000

Cognitive .893 .315 .002

Social .934 .098

Affective .602

Memory

Table (4) (see the appendices) ranks strategy use by individual strategies mean

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scores in a descending order from most to least used. The most frequently used

strategy by all participants was a metacognitive strategy, “I pay attention when

someone is speaking in English” (M = 4.44). In contrast, the least preferred strategy

was affective, “I write down my feelings in a language learning diary” ( M = 2.16).

Among the top ten most used strategies were six metacognitive, two affective (“I

encourage myself to speak in English even when I am afraid of making a mistake”,

(M= 3.77), and “I try to relax whenever I feel afraid of using English”, (M= 3.73),

one compensatory “If I can’t think of an English word, I use a word or a phrase that

means the same thing”, (M = 4.17), and one cognitive “I watch English Language

TV shows spoken in English or go to movies spoken in English”, (M= 4.05) .

4.2 Use of strategy by gender

The second research question deals with the relationship between gender and the use

of language learning strategies. Results of a one-way analysis of variance

(ANOVA)iii did not reveal any significant differences in the overall strategy use

between male and female students (F = .719, p = .39). However, the results for

strategy categories showed that males students, surprisingly, used significantly more

social strategies than female students (F = 3.811, p = .05). As for the other

categories, although there were no significant differences between the two groups,

male students used slightly more memory, cognitive, and metacognitive strategies

than female students, see Table (5).

Table 5. Variation in strategy use by gender

Strategies Male Female F Significance

Mean SD Mean SD

MET 3.89 0.66 3.83 0.71 .196 0.66

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COM 3.36 0.58 3.38 0.62 .039 0.85

COG 3.37 0.46 3.33 0.53 .186 0.67

SOC 3.43 0.75 3.15 0.73 3.81 0.05

AFF 3.14 0.54 3.15 0.74 .007 0.93

MEM 3.10 0.46 2.94 0.60 2.19 0.14

Total 3.39 0.41 3.31 0.52 .719 0.40

4.3 Strategy use by proficiency

Language proficiency in language learning strategies research has been determined

in a multitude of ways. For instance, while a number of researchers used

standardized tests to determine proficiency level (see e.g., Mullin, 1992; Nisbet,

Tindall & Arroyo, 2005; Park, 1997 ), others relied on duration of study in English

medium programs as a measure of proficiency (see e.g., Khalil, 2005; Shmais, 2003;

Magogwe & Oliver, 2007 ).Yet, another group of researchers relied on perceived

proficiency (self-efficacy and self-rating) as a measure of students level in the

foreign language (see e.g., Oxford & Nyikos, 1989; Magogwe & Oliver, 2007;

Shmais, 2003) . A fourth measure used students’ grade point average (GPA) in

English courses to place them in different English proficiency categories (see, e.g.,

Shmais, 2003). In this study, multiple measures of proficiency were utilized,

including students’ GPAs (B and above, C and below), duration of study (freshmen,

sophomores, juniors, and seniors), and self-rating (Good, Fair).

4.3.1 Use of strategy by students’ GPAs

The third research question deals with the relationship between language proficiency

and use of language learning strategies. The students were grouped into two groups:

proficient students averaging B and above, which is relatively speaking close to

80%, and less proficient students, averaging C and below. It should be noted that for

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students to remain in good standing in the English department at SQU, their GPAs

must not drop below C.

A one-way analysis of variance (ANOVA) revealed statistically significant

differences between proficient students and less proficient students in the overall use

of strategies (F = 8.142, p = .005). Overall, the proficient students used more

strategies than the less proficient in all categories of strategies, see Table (6). In

addition to that total use of strategies, significant results were obtained for cognitive

strategies (F = 9.350, p = .003), metacognitive strategies (F = 7.184, p = .008), and

affective strategies (F = 4.350, P = .039). The other groups of strategies did not

show any significant differences between the two groups though the results, as can

be seen in the students’ means, clearly favor the more proficient students, see Table

(6).

Table 6. Variation in strategy use by students’ GPAs

Strategies Proficient Less Proficient F Significance

Mean SD Mean SD

MET 4.03 0.59 3.71 0.74 7.18 .008

COM 3.47 0.52 3.30 0.67 2.59 .111

COG 3.49 0.48 3.22 0.51 9.35 .003

SOC 3.36 0.67 3.14 0.79 2.90 .091

AFF 3.28 0.70 3.03 0.66 4.35 .039

MEM 3.09 0.58 2.91 0.54 3.16 .078

Total 3.47 0.45 3.22 0.50 8.142 .005

4.3.2 Strategy use by study duration

To determine whether duration of study in the English Department has any effect on

use of language learning strategies, students’ answers to the questionnaire were

submitted to a one-way ANOVA. As shown in Table (7), the freshmen group

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consistently used more strategies than any other group. However, data analysis

revealed a significant difference among the four groups only in the use of affective

strategies (F = 2.82, P = .042). To locate where the difference was, the Least

Significance Differences test (LSD) was usediv. The test showed that the Freshmen

group used significantly more affective strategies than both the sophomore and

senior groups (p = .009, p = .03, respectively)

Table 7. Strategy use by study durationStrategie

s

Freshma

n

Sophomor

e

Junio

r

Senio

r

F Significanc

e

Mean SD Mean SD Mea

n

SD Mea

n

SD

MET 4.04 0.5

7

3.78 0.5

9

3.89 0.7

4

3.70 0.7

3

1.5

2

.212

COM 3.60 0.5

1

3.31 0.7

4

3.27 0.5

5

3.35 0.6

3

1.9

5

.126

COG 3.45 0.4

5

3.15 0.5

1

3.36 0.5

2

3.33 0.5

4

1.4

6

.228

SOC 3.43 0.7

3

3.02 0.7

3

3.28 0.6

7

3.15 0.8

1

1.5

4

.207

AFF 3.39 0.6

5

2.89 0.5

1

3.20 0.7

4

3.03 0.6

9

2.8

2

.042

MEM 3.08 0.4

9

2.83 0.6

5

2.96 0.6

5

3.04 0.5

6

0.9

8

.403

Total 3.50 0.3 3.18 0.4 3.34 0.5 3.29 0.5 1.9 .119

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7 8 0 4 9

4.3.3 Strategy use by self-rating

The background questionnaire included a self-rating scale used to determine the

students’ own judgment of their proficiency in English. The students had to rate

their proficiency in English using one of four options: excellent, good, fair, poor.

Only a very small number of students rated themselves as “excellent” or “poor”,

resulting in, as mentioned before, eliminating them from the study. Students’ data

were submitted to a one-way analysis of variance (ANOVA) to determine if there

were any differences between the two groups, “good” and “fair”. ANOVA results

showed that, for all strategies, those students who rated their English language

proficiency as “good” used significantly more strategies than the other group, see

Table (8). Moreover, the “Good” group used every category of strategy more

frequently than the “Fair” group.

Table 8. Variation in strategy use by students’ self-rating

Strategies Good Fair F Significance

Mean SD Mean SD

MET 4.02 0.61 3.57 0.73 13.75 .000

COM 3.52 0.55 3.13 0.63 13.46 .000

COG 3.48 0.46 3.11 0.51 17.24 .000

SOC 3.42 0.71 2.93 0.69 14.66 .000

AFF 3.29 0.69 2.90 0.60 10.27 .002

MEM 3.14 .0.52 2.75 0.54 16.36 .000

Total 3.49 0.45 3.08 0.46 24.14 .000

4.4 Strategies predictive of L2 proficiency

To answer question four and find out which category of learning strategies is

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predictive of (correlated with) L2 proficiency as measured by students’ GPAs, a

backward stepwise logistic regression analysis was performed on students’ data. The

six categories of strategies were specified as the predictor variables with students’

GPAs as the criterion (dependent) variable. A test of the full model with all six

predictors against a constant-only model was statistically reliable, χ2 (1, 128) =

9.172, p = .002), indicating that the predictors, as a set, reliably distinguished

between students with high GPAs and those with low GPAs. The regression model

revealed that only cognitive strategies were significantly correlated with students’

GPAs ( = 1.120, p = .004). In the second step of the analysis, the compensatory

strategies variable was removed, followed by memory strategies, affective strategies,

social strategies, and metacognitive strategies respectively. Table (9) shows

regression coefficients, Wald statistics, exponential Bv (odds ration), and 95%

confidence intervals for odds ratio for each of the six predictors in the first step of

the regression.

Table 9. Backward logistic regression analysis of students’ GPAs as a function of

strategy use

95% confidence

Interval for Odds

Ratio

Variables B Wald

Test

Odds

Ratio

Lower Upper

Memory strategies -1.161 .120 .852 .343 2.114

Cognitive Strategies .966 2.463 2.626 .786 8.770

Compensatory

strategies

.032 .007 1.033 .495 2.154

Metacognitive

strategies

.310 .477 1.363 .566 3.281

Affective Strategies .225 .415 1.252 .632 2.481

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Social Strategies -.214 .354 .808 .400 1.632

5. Discussion

Data analysis reveals several significant findings. First, in general Omani students

favored metacognitive strategies over all other strategies. Second, there were no

significant differences between males and females in the overall use of strategies,

although analysis results showed that male students used significantly more social

strategies than their female counterparts. Third, the more proficient students differed

from the less proficient learners in several ways: (1) they used more overall

strategies; (2) they used more cognitive, metacognitive, and affective strategies than

the less proficient learners. Fourth, freshmen in general used more strategies

followed by juniors, seniors, and sophomores. However, the differences between the

four groups were significant only with regard to affective strategies, where freshmen

used more of these strategies than both sophomores and seniors. Fifth, self-rating

was evidently the strongest factor distinguishing between students. Results

demonstrated that students who perceived themselves as proficient users of the

language (the “Good” group) used significantly more strategies than the other group.

Finally, though students with high GPAs differed from students with low GPAs in

the overall use of strategy, and in the use of cognitive, metacognitive, and affective

strategies, only cognitive strategies, in a regression model analysis, was predictive of

students’ GPAs.

5.1 Overall Strategy use

In general, students in this study reported medium to high use of SILL learning

strategies with a preference for metacognitive strategies, which reflects the students’

endeavor to become proficient in the target language. Among the top ten strategies

used by all participants, six belong to the metacognitive strategies set. These

strategies are essential for successful language learning, since they, as pointed out by

Oxford (1990), help learners coordinate and maximize their own learning process

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through monitoring and evaluating language use, planning, focusing, organizing,

and seeking opportunities to use the language. Considering that maintaining a good

GPA throughout the course of study at the Department is a requirement for

continuation in the program, no wonder that the majority of the students are

instrumentally motivated to learn the language. Accordingly, the use of the various

strategies subsumed under the metacognitive heading seems for all of them to be an

indispensible requirement if they are to graduate from the department with a degree

to qualify them to teach English. The relative high use of metacognitive strategies

has also been reported in other studies, including Hong-Nam & Leavell, 2006;

Magogwe & Oliver, 2007; Nisbet, Tindall & Arroyo, 2005, among others7.

Among the five least favored strategies (low use: 2.4 or below) were one

compensatory strategy (I make up new words if I did not know the right ones I

English), three memory strategies (I use rhymes to remember new English words; I

use flashcards to remember new English words; I physically act out new English

words), and one affective strategy (I write down my feelings in a language learning

diary), occupying the final position. Given that writing diaries is not an

exceptionally popular practice in the Arab World, students’ disdain from this

strategy seems justifiable. The fact that memory strategies were the least favored

strategies is quite surprising considering that the educational system in most of the

Arab countries emphasizes rote memorization. This relatively surprising result may

reflect students’ displeasure with the conservative educational methods and

techniques and their quest for alternative strategies that depart from the conventional

didactic strategies to more communicatively oriented strategies. Moreover, this

result, obtained also by other researchers (e.g., Al-Otaibi, 2004; Khalil, 2005; Hong-

Nam & Leavell, 2006), may underscore the students’ recognition that excelling in

learning a foreign language requires actively involving themselves in the learning

process, seeking opportunities to use the language, cooperating with their peers, etc.

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5.2 Strategy use by gender

Contrary to most research findings (e.g., Hong-Nam & Leavell, 2006; Khalil, 2005;

Oxford, 1990; Oxford & Ehrman, 1995), male students in this study used more

learning strategies than did female students though the differences between the two

groups were not significant in most cases. The only significant difference between

males and females was in their use of social strategies. While one expects female

students to use more social strategies than male students as they generally excel at

establishing strong relationships and building vast social networks (Khalil, 2005),

this was not borne out in this study. A logical explanation for this result can be

attributed to the cultural background of these students. Omani society is organized

into tribes and until recently the tribes, which consist of large extended kin groups

that interact frequently with each other, were of major political and social

importance (Wilkinson, 1987). Men in particular have to develop extremely good

social skills to operate in this context, and even though Oman now has a centralized

and modern government, the tribal units are still central to the organization of

Omani society. Moreover, the conservative nature of culture, customs, and habits

prevents females in the Arab World socializing and establishing relationships

outside their immediate circles, which is a prerequisite for excelling in acquiring a

foreign language within any communicatively oriented approach to language

learning.

5.3 Strategy use by English proficiency

Research examining the use of learning strategies by different proficiency groups

showed a linear relationship between the two factors (e.g. Green and Oxford, 1995;

Khalil, 2005; Wharton, 2000). The present study revealed a complex picture due to

the multitude of measures used to assess language proficiency. In terms of students’

GPAs, the study showed that the more proficient students used significantly more

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overall strategies, cognitive strategies, metacognitive strategies and affective

strategies than the less proficient learners, concurring thus with result obtained by

Nisbet, Tindall & Arroyo (2005). These results show that the proficient learners

seem to be more aware of their language needs; thus, they tend to utilize strategies

that will help them master the target language through practicing, reasoning,

analyzing, as well as strategies that allow them to control their own learning through

planning and evaluating learning. Moreover, these learners exercise a great deal of

control over their emotions and attitudes through lowering their anxiety levels and

increasing their motivation levels. In this regard, Oxford & Nyikos (1989, p. 295)

remark that “language proficiency can be either effects or causes of strategy use.”

They add that “use of appropriate strategies leads to enhanced actual and perceived

proficiency, which in turn creates high self-esteem, which leads to strong

motivation, spiraling to still more use of strategies, great actual and perceived

proficiency, high self-esteem, improved motivation, and so on.”

Many studies showed a positive relationship between strategy use and study

duration. Khalil (2005), for example, revealed that university-level students

reported higher use of almost all strategy categories than did high school students,

which suggests, as pointed out by Magogwe and Oliver (2005p. 346) that “many

strategies may be developmentally acquired.” Hence, the longer the duration of

language study is, the more are the strategies used by learners. This study, however,

showed a curvilinear relationship between duration of study and strategy use. In the

overall use of strategies, freshmen showed a high use of strategies (m= 3.5),

sophomores, on the other hand, demonstrated medium use (m= 3.18), and so did

juniors (m= 3.34) and seniors (m= 3.29). A similar result was obtained by Phillips

(1991). Likewise, Hong-Nam & Leavell (2006, pp. 410-11) explain a similar result

by indicating that once learners reach advanced proficiency levels, “their need to

consciously administer and [become] deliberate about their learning choices

becomes less necessary.” Moreover, “[a]dvanced learners’ habitual and successful

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application of language strategies may be soon internalized that they do not report

what has become for them an automated process;” accordingly they reported less

strategy use than the freshmen group.

As for the different categories of strategies, learners differed significantly in their

use of affective strategies. It might be the case that the freshmen students in this

study realized that learning a second language requires exercising considerable

control over their emotions, motivation, and attitudes; thus, they might have worked

on lowering their anxiety levels and increasing their motivational levels. This type

of control over emotions is critical for these learners considering that their

performance in their first year determines their status in the Department. Failure to

control their emotions might lead to poor performance, which might eventually

result in dismissal from the program. As for the other strategies, the different groups

reflected the same pattern and order of strategy use, whereby metacognitive

strategies occupied the top of the list followed by compensatory strategies, cognitive

strategies, social strategies and affective strategies. This means that, for all groups,

the duration of study effects were relatively marginal.

As for the third proficiency parameter (self-rating), students’ perception of their

linguistic capabilities seems to be the strongest factor distinguishing learners in their

use of strategies. Increase in students’ self-rating translated into significant increases

in their use of all types of strategies. Pajares and Schunk (2001) explain such a result

by suggesting that high self-efficacy beliefs are associated with high achievement

and indicated that high strategy use is an attribute of a good language learner. In this

study, learners with high self-rating reported high strategy use of three categories

(metacognitive, compensatory, and cognitive); on the other hand, the fair learners

reported high use of only metacognitive strategies. This result seems to show that

the higher the students’ self-perceived proficiency, the more likely they were to

exercise control over their learning than the students with lower self-perceived

proficiency. Accordingly, they are more likely to use strategies that would help them

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organize, plan, monitor, focus, and evaluate their learning. Moreover, they are more

likely to use compensatory strategies than the other group, since these strategies

generally help learners use the language to overcome any limitations and gaps in

their linguistic knowledge through guessing, making up new words, and using

circumlocution and synonyms.

5.4 Strategies predictive of success in L2

The regression model used to analyze students’ data revealed that cognitive

strategies are significantly correlated with proficiency, measured using students’

GPAs in English courses. This result concurs with Park (1997) who showed that

social and cognitive strategies predicted TOEFL scores among Asian students.

Examples of the cognitive strategies include item 13 “I use the English words I

know if different ways,” item 20 “I try to find patterns in English,” and item 22 “I

try not to translate word for word.” These strategies and many others subsumed

under the cognitive heading help students practice, analyze, revise their language,

create structures, and look for opportunities to use the language. These strategies are

critical for success in learning English, and they are the type of strategies language

learners in the English Department usually focus on.

6. Conclusion

In general, while some of the results reported here are consistent with the findings of

previous research on strategy use (Green & Oxford, 1995: O’Malley & Chamot,

1990; Park, 1997), the current study reveals a more complex pattern of strategy use

than has been observed in previous studies. Like previous research (e.g., Khalil,

2005; Shmais, 2003), the current results demonstrate unequivocally that English

students at SQU were aware of the significance of learning strategies to the

development of their proficiency in English; the students used learning strategies

with a medium to high frequency, with metacognitive strategies ranking highest

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among all strategies. In all comparisons, metacognitive strategies, which help

student direct, organize, and plan their learning, were favored by all students over all

other strategies. A similar result was obtained by Shmais (2003) and Hong-Nam &

Leavell ( 2006 ), showing that students overall prefer metacognitive strategies over

other strategies, and the least preferred strategies were affective and memory

strategies. The use of metacognitive strategies must be supported in curricula design,

especially through the beginning stages of learning a second/foreign language,

where obtaining some type of declarative knowledge is critical in order to create

“heightened understanding of the what and how of successful language learning”

(Hong-Nam & Leavell, 2006, p. 412).

Unlike many previous studies (see e.g., Khalil, 2005), this study did not reveal any

significant differences between male and female students except in their use of

social strategies, unexpectedly favoring male students. While one would expect

female students to utilize their superior social skills to establish social networks that

would assist them in the process of learning, male students showed higher

preference for these strategies than their female counterparts, which means they

were more likely to interact, cooperate, and empathize with others. This, as

explained previously, is probably due to disparity in social expectations placed on

both groups.

With regard to the relationship between strategy use and proficiency, the results

showed that proficiency had a main effect on the overall strategies used by learners

as well as on three categories, namely cognitive, metacognitive, and affective

strategies, favoring proficient students. As for the effects of study duration, it only

had a significant effect on the use of affective strategies, showing higher use of these

strategies by freshmen students. Of all factors examined in this study, self-rating was

the strongest predictor of differences among learners. Unlike Magogwe & Oliver

(2007), who showed a weak relationship between self-efficacy beliefs and the

overall use of language learning strategies, this study showed that students with high

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self-rating reported more strategy use than those with fair self-rating. Future

research in this area should focus on the interaction between self-rating and

proficiency to investigate various combinations and how they relate to strategy use;

for example, how someone with low proficiency and high self-rating will compare

to someone who has low high proficiency but low self-rating and so on.

The results of the present study highlight the importance of incorporating strategy

training into L2 classroom instruction and into curriculum design. Accordingly, both

students and teachers are required to develop awareness of these various strategies

through appropriate instruction or training for both groups. Becoming aware of their

preferred learning strategies might help learners become more independent and

effective in approaching the task of learning a second language. Oxford (2001 p. 1,

as cited in Nisbet et al., 2005) emphasizes the importance of such autonomy by

stating that learning strategies “are aimed at self-management in language learning

and self-reliance in language use.” Moreover, explicit training in strategy use might

be necessary so as to allow students at different levels and those with different

proficiency levels and learning styles to practice a wide range of these strategies that

are “appropriate to different instructional task and activities that constitute an

essential part of the classroom L2 experience” (Khalil, 2005 p. 115). This stipulates

that learners at different levels require variable degrees of teacher’s intervention in

the learning process. Accordingly, for less proficient learners, high levels of explicit

instruction in strategy use might be essential to raise learners’ awareness of the

significance of developing their strategic competence. Thus, the teacher’s role is

critical. “Effective teachers should consider each learning task from a novice’s

perspective and scaffold the learning process through purposeful strategy choice”

(Hong-Nam & Leavell, 2006, p.412). Cohen, Weaver, & Li (1995, p.29) emphasized

that approach by pointing out that “explicitly describing, discussing, and reinforcing

strategies in the classroom can have a direct payoff on student outcomes.” As

learners develop some explicit knowledge of various strategies, and as they become

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relatively autonomous, the teacher’s role changes to a facilitator who selects the

strategies, which are appropriate for various tasks and are suitable for different

individuals. This eventually might help learners gain more independence and

develop confidence, which, in turn, will enhance their linguistic abilities. To achieve

this, it is critically important to provide teachers with the proper training in strategy

assessment and instruction, through the systematic introduction and reinforcement of

learning strategies that help learners improve their proficiency in the target language

(Cohen, Weaver & Li, 1995).

In terms of curriculum design and material preparation, researchers have often

recommended that strategy training be integrated into language curriculum (see e.g.,

Khalil, 2005; Oxford, 1990; Tyacke, 1991). Therefore, teachers and materials’

developers should incorporate a variety of tasks and activities, which target

strategies that teachers view as critical for success in learning a second language.

The fact that students with different proficiency levels utilize different learning

strategies must guide the development of instructional materials (Chamot &

O’Malley, 1996). These materials, according to Khalil (2005, p. 115), should

provide “students with further opportunities to practice a wide variety of strategies

that are appropriate to different instructional tasks and activities that constitute an

essential part of the classroom L2 experience.” Moreover, instructional materials

might be developed to target certain strategies which research finds essential for

success in learning a second language. In this regard, Ellis and Sinclair (1989)

advocated the use of organization strategies, risk-taking strategies, and personal

strategies in content-based instruction. Chamot and O’Malley (1996) also dev

eloped instructional materials which incorporated explicit instruction in learning

strategies.

In conclusion, a number of variables were considered in assessing Omani students’

use of learning strategies. While these variables may explain to some extent

discrepancies in strategy use among various groups of learners, other factors that

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might affect the use of LLS such as the role of beliefs, social and cultural

background, motivation, attitude, personality, etc. must be as well studied to find out

their interaction with strategy use. Moreover, further research in this area is critical

to the development of teacher training and student instruction in order to base these

two components on firm theoretical and empirical foundations.

7. Limitations of this study

One of the limitations of the study is lack of a standardized English proficiency test.

To determine students’ proficiency, the study utilized different constructs such as

students’ GPAs, students’ self-rating, and duration of study, which may account for

the apparent contrasts in the results reported for each measure. Another limitation is

the complete reliance on SILL to determine strategies used by students. While this

quantitative measure is very beneficial, the students “may not remember the

strategies they have used in the past, may claim to use strategies that in fact they do

not use, or may not understand the strategy descriptions in the questionnaire items

(Chamot, 2004 p.15). Accordingly, the SILL should be supplemented with other

techniques such as think-aloud protocols concurrent with a specific learning task,

written diaries, stimulated recall interviews, and other methods which might provide

richer and more sample-specific data.

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Notesi Many studies (see, e.g., Shmais, 2003) use GPA as a predictor of language proficiency. Theassumption in such studies is that the higher the GPA, the more proficient the learner in the foreignlanguage is.ii Hatch and Lazaraton (1991: 310) maintain that when the cell sizes are unbalanced, “the assumptionof equal variance may be violated.”iii It should be noted that ANOVA gives exactly the same results as the t-test.iv Despite the significant difference among the four groups (F = 0.98, p = .042), Schaffé post-hoc test

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showed tendency of difference, but it was not significant. As a result, LSD, which can locatedifferences when the mean differences are not big.v In step 1 of the regression analysis, the exponential B indicates that the odds of having a higherGPA increased by a factor of 2.626 with every point on a five-point Likert scale in the case ofcognitive strategies. This ration jumped to 3.065 in the final step.

AppendicesLanguage Learning Strategies Questionnaire

Dear student,

This questionnaire is an attempt to explore the language learning strategies used by thestudents of the English Department at SQU. Your participation in this study and honestresponses to the questionnaire items are highly appreciated. Please be assured that yourinformation will remain strictly confidential and will be used solely for the purpose of thisresearch project.

Part One:

1. Name: ____________________________ ID: __________

2. Gender: Male Female

2. Year in the English Department: First SecondThird Fourth

3. Program: Education ArtTranslation

4. Overall GPA: _________

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5. GPA in English courses: ___________

6. Language(s) spoken at home: ______________________________

7. How do you rate your proficiency in English? Excellent Good FairPoor

B. Directions:

This form of the Strategy Inventory for Language Learning (SILL) is for students of English asa foreign language. You will find statements about learning English. Please read eachstatement carefully. Then, next to each statement, make a check mark (√) in the answerbox that tells

how true of you the statement is.

1. Never or almost never true of me ( (لاینطبق علي أبدا

2. Seldom true of me ( (نادرا ما ینطبق علي

3. Sometimes true of me ( (أحیانا ینطبق علي

4. Often true of me ( (عادة ینطبق علي

5. Always or almost always true of me ( (دائما ینطبق علي

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1

Never

2

Seldom

3

Sometimes

4

Often

5

Always

1 I think of relationships betweenwhat I already know and newthings I learn in English

2 I use new English words in asentence so I can rememberthem.

3 I connect the sound of a newEnglish word and an image orpicture of the word to help meremember the word.

4 I remember a new English wordby making a mental picture ( صورةذھنیة ) of a situation in which theword might be used.

5 I use rhymes ( to (كلمات مسجعةremember new English words.

6 I use flashcards ( البطاقات )toremember new English words.

7 I physically act out (أقوم بتمثیل )new English words.

8 I review English lessons often.

9 I remember new English wordsor phrases by remembering theirlocation on the page, on theboard, or on a street sign.

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10 I say or write new English wordsseveral times.

11 I try to talk to native Englishspeakers.

12 I practice the sounds of English.

13 I use the English words I know indifferent ways.

14 I start conversations in English.

15 I watch English Language TVshows spoken in English or go tomovies spoken in English

16 I read for pleasure in English.

17 I write notes, messages, letters,or reports in English.

18 I first skim an English passage(read over the passage quickly)then go back and read carefully.

19 I look for words in my ownlanguage that are similar to newwords in English.

20 I try to find patterns ( (أنماط متكررةin English.

21 I find the meaning of an Englishword by dividing it into parts thatI understand.

22 I try not to translate word-for-

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word.

23 I make summaries of informationthat I hear or read in English.

24 To understand unfamiliar words,I make guesses.

25 When I can’t think of a wordduring a conversation in English,I use gestures

( (اشارات .

26 I make up ( new words if I (أختلقdon’t know the right ones inEnglish.

27 I read English without looking upevery new word.

28 I try to guess what the otherperson will say next in English.

29 If I can’t think of an English word,I use a word or a phrase thatmeans the same thing.

30 I try to find as many ways as I canto use my English.

31 I notice my English mistakes anduse that information to help medo better.

32 I pay attention when someone isspeaking English.

33 I try to find out how to be abetter learner of English.

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34 I plan my schedule so I will haveenough time to study English.

35 I look for people I can talk to inEnglish.

36 I look for opportunities to readas much as possible in English.

37 I have clear goals for improvingmy English skills.

38 I think about my progress inlearning English.

39 I try to relax whenever I feelafraid of using English.

40 I encourage myself to speak inEnglish even when I am afraid ofmaking a mistake.

41 I give myself a reward or treatwhen I do well in English.

42 I notice if I am tense or nervouswhen I am studying or usingEnglish.

43 I write down my feelings in alanguage learning diary.

44 I talk to someone else about howI feel when I am learning English.

45 If I don’t understand somethingin English, I ask the other personto slow down or say it again.

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46 I ask English speakers to correctme when I talk.

47 I practice English with otherstudents.

48 I ask for help from Englishspeakers.

49 I ask questions in English.

50 I try to learn about the culture ofEnglish speakers.

Table 4. Preference of language learning strategies by their means

Rank Strategy

No.

Strategy

Category

Strategy Statement Mean

High usage ( M = 3.5 -5.0)

1 32 MET I pay attention when someone is speaking

English4.44

2 38 MET I think about my progress in learning English 4.20

3 33 MET I try to find out how to be a better learner of

English.

4.19

4 29 COM If I can’t think of an English word, I use a word

or a phrase that means the same thing.

4.17

5 31 MET I notice my English mistakes and use that

information to help me do better.4.08

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6 15 COG I watch English Language TV shows spoken in

English or go to movies spoken in English.

4.05

7 30 MET I try to find as many ways as I can to use my

English.

3.79

8 40 AFF I encourage myself to speak in English even

when I am afraid of making a mistake.3.77

9 39 AFF I try to relax whenever I feel afraid of using

English.

3.73

10 37 MET I have clear goals for improving my English

skills.

3.71

11 24 COM To understand unfamiliar words, I make guesses. 3.64

12 1 MEM I think of relationships between what I already

know and new things I learn in English.

3.62

13 27 COM I read English without looking up every new

word.

3.61

14 16 COG I read for pleasure in English. 3.59

15 36 MET I look for opportunities to read as much as

possible in English.3.55

16 12 COG I practice the sounds of English. 3.53

Medium usage ( M = 2.5-3.4)

17 17 COG I write notes, messages, letters, or reports in

English.

3.49

18 45 SOC If I don’t understand something in English, I ask

the other person to slow down or say it again.

3.49

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19 9 MEM I remember new English words or phrases by

remembering their location on the page, on the

board, or on a street sign.

3.48

20 21 COG I find the meaning of an English word by

dividing it into parts that I understand.3.46

21 49 SOC I ask questions in English. 3.45

22 42 AFF I notice if I am tense or nervous when I am

studying or using English.

3.44

23 10 COG I say or write new English words several times. 3.41

24 18 COG I first skim an English passage (read over the

passage quickly) then go back and read carefully.

3.40

25 13 COG I use the English words I know in different ways. 3.37

26 35 MET I look for people I can talk to in English. 3.37

27 19 COG I look for words in my own language that are

similar to new words in English.3.35

28 34 MET I plan my schedule so I will have enough time to

study English.3.34

29 47 SOC I practice English with other students. 3.31

30 28 COM I try to guess what the other person will say next

in English.

3.30

31 50 SOC I try to learn about the culture of English

speakers.3.29

32 3 MEM I connect the sound of a new English word and

an image or picture of the word to help me

remember the word.

3.29

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33 2 MEM I use new English words in a sentence so I can

remember them.

3.26

34 8 MEM I review English lessons often. 3.19

35 4 MEM I remember a new English word by making a

mental picture of a situation in which the word

might be used.

3.15

36 22 COG I try not to translate word-for-word. 3.10

37 25 COM When I can’t think of a word during a

conversation in English, I use gestures.

3.09

38 14 COG I start conversations in English. 3.08

39 44 AFF I talk to someone else about how I feel when I am

learning English.

3.05

40 11 COG I try to talk to native English speakers. 3.03

41 20 COG I try to find patterns in English. 3.02

42 48 SOC I ask for help from English speakers. 3.00

43 46 SOC I ask English speakers to correct me when I talk. 2.88

44 23 COG I make summaries of information that I hear or

read in English.

2.87

45 41 AFF I give myself a reward or treat when I do well in

English.

2.73

Low usage (M = 2.4 or below)

46 26 COM I make up new words if I don’t know the right

ones in English.

2.43

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47 5 MEM I use rhymes to remember new English words. 2.39

48 6 MEM I use flashcards to remember new English words. 2.35

49 7 MEM I physically act out new English words. 2.20

50 43 AFF I write down my feelings in a language learning

diary.

2.16

MET (Metacognitive strategies), COG (Cognitive strategies), MEM (Memory strategies),

COM (Compensatory strategies), SOC (Social Strategies), AFF (Affective Strategies).

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_____

Footnotes1 Many studies (see, e.g., Shmais, 2003) use GPA as a predictor of languageproficiency. The assumption in such studies is that the higher the GPA, the moreproficient the learner in the foreign language is.2 Htch and Lazaraton (1991: 310) maintain that when the cell sizes are unbalanced,“the assumption of equal variance may be violated.”3 It should be noted that ANOVA gives exactly the same results as the t-test.4 Despite the significant difference among the four groups (F = 0.98, p = .042),Schaffé post-hoc test showed tendency of difference, but it was not significant. As aresult, LSD, which can locate differences when the mean differences are not big.5 In step 1 of the regression analysis, the exponential B indicates that the odds ofhaving a higher GPA increased by a factor of 2.626 with every point on a five-pointLikert scale in the case of cognitive strategies. This ration jumped to 3.065 in thefinal step.